本文用 Python 实现 PS 图像调整中的亮度调整，具体的算法原理和效果可以参考之前的博客：
http://www.zzvips.com/article/178695.html
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import matplotlib.pyplot as pltfrom skimage import iofile_name='D:/Image Processing/PS Algorithm/4.jpg';img=io.imread(file_name)Increment = -10.0img = img * 1.0I = (img[:, :, 0] + img[:, :, 1] + img[:, :, 2])/3.0 + 0.001mask_1 = I > 128.0r = img [:, :, 0]g = img [:, :, 1]b = img [:, :, 2]rhs = (r*128.0 - (I - 128.0) * 256.0) / (256.0 - I) ghs = (g*128.0 - (I - 128.0) * 256.0) / (256.0 - I)bhs = (b*128.0 - (I - 128.0) * 256.0) / (256.0 - I)rhs = rhs * mask_1 + (r * 128.0 / I) * (1 - mask_1)ghs = ghs * mask_1 + (g * 128.0 / I) * (1 - mask_1)bhs = bhs * mask_1 + (b * 128.0 / I) * (1 - mask_1)I_new = I + Increment - 128.0mask_2 = I_new > 0.0R_new = rhs + (256.0-rhs) * I_new / 128.0G_new = ghs + (256.0-ghs) * I_new / 128.0B_new = bhs + (256.0-bhs) * I_new / 128.0R_new = R_new * mask_2 + (rhs + rhs * I_new/128.0) * (1-mask_2)G_new = G_new * mask_2 + (ghs + ghs * I_new/128.0) * (1-mask_2)B_new = B_new * mask_2 + (bhs + bhs * I_new/128.0) * (1-mask_2)Img_out = img * 1.0Img_out[:, :, 0] = R_newImg_out[:, :, 1] = G_newImg_out[:, :, 2] = B_newImg_out = Img_out/255.0# 饱和处理mask_1 = Img_out < 0mask_2 = Img_out > 1Img_out = Img_out * (1-mask_1)Img_out = Img_out * (1-mask_2) + mask_2plt.figure()plt.imshow(img/255.0)plt.axis('off')plt.figure(2)plt.imshow(Img_out)plt.axis('off')plt.figure(3)plt.imshow(I/255.0, plt.cm.gray)plt.axis('off')plt.show() |
总结
以上所述是小编给大家介绍的Python实现 PS 图像调整中的亮度调整 ,希望对大家有所帮助，如果大家有任何疑问请给我留言，小编会及时回复大家的。在此也非常感谢大家对服务器之家网站的支持！
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